Addressing cellular heterogeneity in tumor and circulation for refined prognostication

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Addressing cellular heterogeneity in tumor and circulation for refined prognostication
Title:
Addressing cellular heterogeneity in tumor and circulation for refined prognostication
Journal Title:
Proceedings of the National Academy of Sciences of the United States of America
Keywords:
Publication Date:
15 August 2019
Citation:
Addressing cellular heterogeneity in tumor and circulation for refined prognostication Su Bin Lim, Trifanny Yeo, Wen Di Lee, Ali Asgar S. Bhagat, Swee Jin Tan, Daniel Shao Weng Tan, Wan-Teck Lim, Chwee Teck Lim Proceedings of the National Academy of Sciences Sep 2019, 116 (36) 17957-17962; DOI: 10.1073/pnas.1907904116
Abstract:
Despite pronounced genomic and transcriptomic heterogeneity in non–small-cell lung cancer (NSCLC) not only between tumors, but also within a tumor, validation of clinically relevant gene signatures for prognostication has relied upon single-tissue samples, including 2 commercially available multigene tests (MGTs). Here we report an unanticipated impact of intratumor heterogeneity (ITH) on risk prediction of recurrence in NSCLC, underscoring the need for a better genomic strategy to refine prognostication. By leveraging label-free, inertial-focusing microfluidic approaches in retrieving circulating tumor cells (CTCs) at single-cell resolution, we further identified specific gene signatures with distinct expression profiles in CTCs from patients with differing metastatic potential. Notably, a refined prognostic risk model that reconciles the level of ITH and CTC-derived gene expression data outperformed the initial classifier in predicting recurrence-free survival (RFS). We propose tailored approaches to providing reliable risk estimates while accounting for ITH-driven variance in NSCLC.
License type:
PublisherCopyrights
Funding Info:
This work was conceived and carried out at the MechanoBioEngineering Laboratory at the Department of Biomedical Engineering, National University of Singapore (NUS). We acknowledge support provided by the Institute for Health Innovation and Technology (iHealthtech) at NUS. We thank Dr. Won-Chul Lee and Dr. Jianjun Zhang at the MD Anderson Cancer Center for providing multiregion profiling data and Dr. Goh Kah Yee at National Cancer Centre Singapore and Mr. Terence Cheng at Institute of Molecular and Cell Biology for providing lung cancer cell lines. W.-T.L. is supported by the National Medical Research Council (NMRC/CSA/040/2012 and NMRC/CSA-INV/0025/2017). S.B.L. acknowledges support provided by the NUS Graduate School for Integrative Sciences and Engineering, Mogam Science Scholarship Foundation, and Daewoong Foundation.
Description:
The full paper is available for download at the publisher's URL: https://doi.org/10.1073/pnas.1907904116
ISSN:
0027-8424
1091-6490
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